自动驾驶汽车整车在环仿真测试平台-2023-03-自动驾驶

第二届车路协同自动驾驶论坛(The2ndForumofCAV-HighwaySystems)弘毅明德笃学创新Prof.ZhigangXu/deputydirectorInternetofvehicleLabsponsoredbyMinistryofEducationandChinaMobileChang’anUniversity.长安大学车联网教育部-中国移动车联网实验室徐志刚副主任/教授njing弘毅明德笃学创新WhyweneedtotesttheautonomousvehicleWhatcanwelearnfromexistingexperiences现有测试方法研究3.TheproposedHILSimulationtestplatformandongoingwork智能汽车硬件在环测试平台4.Opportunitiesandchallenges机遇与挑战弘毅明德笃学创新1、Whyweneedtotesttheautonomousvehicle为什么要进行智能汽车测试弘毅明德笃学创新Thedevelopmentofautonomousvehicles(AV)caneffectivelyreducetrafficaccidents&energyconsumption,improvetrafficefficiency,andfreethedriverfromboringdrivingtasks.弘毅明德笃学创新1.2Accidents&SafetyItisimminenttoestablishacompletetest&evaluationframeworkforicalscenariosforAVse弘毅明德笃学创新tsTest12.5yearsTestyears1.09deaths/100millionmilesaccidentrateaccidentrateaccuracy:95%performanceofAVexceeds20%ofHVThedrivingenvironmentishighlyuncertain,non-repeatable,unpredictableandinexhaustibleeportoftheRANDCorporationstatesTraditionalautomotivesafetytestingmethodshavebeenisnecessarytostudynewtestingtheoriesanddesignnewtestingmethods.HowtorealizetherapidtestofAVs,improvingtestefficiency&reducingtest弘毅明德笃学创新2、Whatcanwelearnfromexistingexperiences现有测试工具研究弘毅明德笃学创新ISO26262.Repeatable、Extreme&DangerousConditions、Accelerate弘毅明德笃学创新Consistsofsimulationscenarios,vehicledynamicsmodel,sensormodel,planningdecisionalgorithm,etc.Getridoftheneedforrealtestenvironmentandhardware.Generallyappliedintheearlystagesoffunctionaldevelopment.Highefficiency&Lowcost、risk&ShortperiodThetestresultsareheavilydependentonthethesensormodelandthevehiclemodel.Rapidrestorationofreal-worldscenariosenvironmentisdifficulttoachievecorrectnessofinsimulatedAirSimApollooo弘毅明德笃学创新FieldtestFromtheenvironmenttothevehiclesarephysical.Flexibleintegrationofscenariosandenvironments.Multiplescenariosandtestcases.LowefficiencyLongperiod 弘毅明德笃学创新Somepartsorsystemsarereal,andtheenvironmentisvirtual.Acceleratethetestingprocess.Improvethetestefficiency.Realistictestresults.SeveralHILtestingtechniquesarerelativelycomplexandcostly,suchasLiDAR,infraredcameras,etc.Thescopeofapplicationisstilllimited弘毅明德笃学创新ationtestplatformandongoingwork智能汽车硬件在环测试平台弘毅明德笃学创新ChanganUniversitymainlyconductsfunctional&performancetesting,safety&reliabilitytesting,andachievescomprehensiverapidvalidationofsafety,sindoorsgTestSite弘毅明德笃学创新mVirtualSimulationTestScenarioe弘毅明德笃学创新mFrontAxleRotatableDrumTestBenchSimulaterealroadphysicalenvironmentindoors:CurvedsimulationwithmultidegreeoffreedomarchitectureturedynamicsimulationPavementadhesioncoefficientadjustment(snowyroad,slipperyroad)hanglerollangleandyawangleCollectdatasuchasspeed,wheelangleandhorizontal/longitudinalslope弘毅明德笃学创新mSensorintheLoopSimulationMillimeterWaveRadarintheLoopSimulation:ionofVirtualMMWRadarionRealMMWRadarionGeometricmodelestimationPhysicalmodelRadarmodelGeometricmodelestimationPhysicalmodelRadarmodelTargetmodelEnvironmentmodel弘毅明德笃学创新mSensorintheLoopSimulationMillimeterWaveRadarintheLoopSimulation:ting弘毅明德笃学创新mSensorintheLoopSimulationMillimeterWaveRadarintheLoopSimulation: CarCameraCarCarCameraCarCameraVirtualTrafficScenarioCarCamera弘毅明德笃学创新mSensorintheLoopSimulationCameraintheLoopSimulation:CameraofAVSchemeofCameraofAVDataDataProcessingUnitDataDataProcessingUnitVirtVirtualCameraDataDataProcessingUnit弘毅明德笃学创新mSensorintheLoopSimulationCameraintheLoopSimulation:CameraObscuraSchemeofCameraCameraObscuraVirtualVirtualTrafficScenarioVirtVirtualCameraCameraCameraofAVaalHDCamera弘毅明德笃学创新mSensorintheLoopSimulationCameraintheLoopSimulation:ramSensorintheLoopSimulationLiDARintheLoopSimulation:CollectedPointCloudinRealScenarioGenerated3DScenarioGeneratedPointCloudbySimulatedLiDARintCloudbySimulatedLiDARontestontest弘毅明德笃学创新mTestSituationonditionroad车硬件在环仿真测试平台弘毅明德笃学创新ionoftestingenvironment令ReconstructionofLiDARdata令reconstructionofCameradata令ReconstructionofMMWRadardata令ConstructionofHigh-precisionmap令Synchronizationofdatafvehiclesenvironment令Roadmodeling令Vehicledynamicsandkinematics令Pedestrian,obstaclesimulation令Simulationofdangerousscenes令Pedestrian-Vehicle-Roadcoordination令Quantificationofintelligence令Descriptionofthesemanticnetwork令Man-machinegame令Learningabilitytest令Endurancetest车硬件在环仿真测试平台弘毅明德笃学创新andchallenges总结与挑战Conclusions1.AVILworkbenchintegratingvehicle,simulatedroadsystemsandsensorswasestablished,whichcanbeusedtoverifythefunctionsandperformanceofanautonomousvehicle.开发了一种集成车辆、虚拟场景、模拟传感器的室内无人车快速测试台，可以用于无人车功能验证和性能测试。2.Threetypesofsimulatedsensormodels(MMWRadar,RGBCameraandLiDAR)areconstructed,whichcanfeedtheperceptiondataofthesimulatedscenariostothedecisionalgorithmofthetestedautonomousvehicle.构建了三种传感器仿真模型(毫米波、RGB彩色摄像头、激光雷达)，可以为无人的决策算法测试提供多种类型的感知数据。3.SomeexperimentsonsimplescenariossuchasACC,AEBandLKPhavebesuccessfullyconductedontheproposedworkbench,whichisprovedthattheproposedwor